Nonparametric tests for constant tail dependence with an application to energy and finance

Axel Bücher, Stefan Jäschke and Dominik Wied

Journal of Econometrics, 2015, vol. 187, issue 1, 154-168

Abstract: New tests for detecting structural breaks in the tail dependence of multivariate time series using the concept of tail copulas are presented. To obtain asymptotic properties, we derive a new limit result for the sequential empirical tail copula process. Moreover, consistency of both the tests and a break-point estimator are proven. We analyze the finite sample behavior of the tests by Monte Carlo simulations. Finally, and crucial from a risk management perspective, we apply the new findings to datasets from energy and financial markets.

Keywords: Break-point detection; Multiplier bootstrap; Tail dependence; Weak convergence (search for similar items in EconPapers)
JEL-codes: C12 C14 C32 C58 G32 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407615000263
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Nonparametric tests for constant tail dependence with an application to energy and finance (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:187:y:2015:i:1:p:154-168

DOI: 10.1016/j.jeconom.2015.02.002

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().